I’m a Computer Science graduate with over 2 years of experience, specializing in LLMs, NLP, and Voice/Chat Agents using Whisper, Vapi (STT/TTS), LangChain, RAG, and similar frameworks. I’m experienced with OpenAI, Gemini, and other API integrations, as well as model training, fine-tuning, and hyperparameter optimization. Skilled in AI workflow automation using FastAPI, n8n, Make, and related tools, I build scalable, production-ready AI systems that blend QA precision with innovation for reliable automation.
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• Built a real-time computer vision system to analyze marketing visuals using YOLOv8, OpenCV, and DeepFace for brand logo detection, emotional response analysis, and ad quality scoring.
• Deployed as a FastAPI microservice, producing performance insights for marketing teams.
• Developed an interactive analytics chatbot capable of querying internal datasets using NLP and LangChain’s SQL agents.
• Integrated OpenAI and Gemini APIs for conversational data summarization, enabling managers to retrieve KPIs and insights through natural language queries.
• Developed an AI-powered document processing and retrieval system that uses LLMs and RAG pipelines (LangChain + FAISS) to understand, summarize, and answer user queries from long documents.
• Integrated OpenAI/Gemini APIs for context-aware Q&A, summarization, and insight extraction; deployed via FastAPI for internal enterprise use.
• Built a voice-enabled AI assistant for customer support using Whisper for STT, LLM-based intent handling, and Coqui TTS/gTTS for voice replies.
• Automated ticket creation and escalation through n8n workflows, integrating with Slack and CRM systems for seamless customer query handling.
• Designed a developer productivity tool that analyzes codebases using OpenAI GPT models for bug detection, optimization suggestions, and documentation generation.
• Integrated FastAPI endpoints and automated version tracking through Git hooks; improved review efficiency and reduced manual QA cycles.
• Engineered an AI recruitment automation system integrating LLMs, NLP, and vector-based embeddings for automated resume parsing, skill extraction, and candidate ranking, significantly reducing manual HR effort and bias.
• Developed an AI-powered voice interview module using Whisper for real-time Speech-to-Text, LLM-based intent recognition, and Coqui TTS / gTTS for natural conversational dialogue.
• Implemented multimodal confidence analysis using OpenCV, MediaPipe, DeepFace, and sentiment/prosody analysis models to assess candidate confidence, tone, and communication delivery.
• Generated candidate performance scores and automated the scheduling of manual second-round technical interview.
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